; indeed, in this approach the notion of memory is inextricably bound up with task processing. These representations reveal a rich structure, which allows them to be highly context-dependent while also expressing generalizations across classes of items. These representations suggest a method

for encoding knowledge on Web pages to make it understandable to electronic agents searching for information. The Defense Advanced Research Projects Agency (DARPA), in conjunction with the W3C, is developing DARPA Agent Markup Language (DAML) by extending RDF with more expressive constructs aimed

In recent years, many central banks have placed increased emphasis on price stability. Monetary policy—whether expressed in terms of interest rates or growth of monetary aggregates—has been increasingly geared toward the achievement of low and stable inflation. Central bankers and most other

We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse

for this state of affairs is that existing theories of work The authors express great appreciation to members of the consulting firm that helped us gain access to the organizations where this research was conducted; to Kenneth Brousseau, Daniel Feldman, and Linda Frank for assistance in data collection

We present a novel language for querying object-oriented databases. The language is built around the idea of extended path expressions that substantially generalize [ZAN83], and on an adaptation of the first-order formalization of object-oriented languages from [KW89, KLW90, KW92]. The language

Microarrays are a novel technology that facilitates the simultaneous measurement of thousands of gene expression levels. A typical microarray experiment can produce millions of data points, raising serious problems of data reduction, and simultaneous inference. We consider one such experiment

tiply connected networks: When loops are present, the network is no longer singly connected and local propaga tion schemes will invariably run into trouble . We believe there are general undiscovered theorems about the performance of belief propagation on loopy DAGs. These theo rems, which may have

intractable in the presence of acyclic TBoxes, it remains tractable in EL even with general concept inclusion axioms (GCIs). On the one hand, we extend the positive result for EL by identifying a set of expressive means that can be added to EL without sacrificing tractability. On the other hand, we show

training sentence to inform the model about an exponential number of semantically neighboring sentences. The model learns simultaneously (1) a distributed representation for each word along with (2) the probability function for word sequences, expressed in terms of these representations. Generalization